I. Field
The present invention pertains generally to communications systems, and more specifically to interleavers used in for turbo coding schemes in digital communication systems.
II. Background
Transmission of digital data is inherently prone to interference, which may introduce errors into the transmitted data. Error detection schemes have been suggested to determine as reliably as possible whether errors have been introduced into the transmitted data. For example, it is common to transmit data in packets and add to each packet a cyclic redundancy check (CRC) field, for example of a length of sixteen bits, which carries a checksum of the data of the packet. When a receiver receives the data, the receiver calculates the same checksum on the received data and verifies whether the result of the calculation is identical to the checksum in the CRC field.
When the transmitted data is not used on-line, it is possible to request retransmission of erroneous data when errors are detected. However, when the transmission is performed on-line, such as, e.g., in telephone lines, cellular phones, remote video systems, etc., it is not possible to request retransmission.
Convolutional codes have been introduced to allow receivers of digital data to correctly determine the transmitted data even when errors may have occurred during transmission. The convolutional codes introduce redundancy into the transmitted data and pack the transmitted data into packets in which the value of each bit is dependent on earlier bits in the sequence. Thus, when errors occur, the receiver can still deduce the original data by tracing back possible sequences in the received data.
To further improve the performance of a transmission channel, some coding schemes include interleavers, which mix up the order of the bits in the packet during coding. Thus, when interference destroys some adjacent bits during transmission, the effect of the interference is spread out over the entire original packet and can more readily be overcome by the decoding process. Other improvements may include multiple-component codes that encode the packet more than once, in parallel or in series. For example, it is known in the art to employ an error correction method that uses at least two convolutional coders in parallel. Such parallel encoding is commonly referred to as turbo coding.
For multiple-component codes, optimal decoding is often a very complex task, and may require large periods of time not usually available for on-line decoding. Iterative decoding techniques have been developed to overcome this problem. Rather than determining immediately whether received bits are zero or one, the receiver assigns each bit a value on a multilevel scale representative of the probability that the bit is one. A common scale, referred to as log-likelihood ratio (LLR) probabilities, represents each bit by an integer in some range, e.g., {−32,31}. A value of 31 signifies that the transmitted bit was a zero with very high probability, and a value of −32 signifies that the transmitted bit was a one, with very high probability. A value of zero indicates that the logical bit value is indeterminate.
Data represented on the multilevel scale is referred to as “soft data,” and iterative decoding is usually soft-in/soft-out, i.e., the decoding process receives a sequence of inputs corresponding to probabilities for the bit values and provides as output corrected probabilities, taking into account constraints of the code. Generally, a decoder that performs iterative decoding uses soft data from former iterations to decode the soft data read by the receiver. During iterative decoding of multiple-component codes, the decoder uses results from decoding of one code to improve the decoding of the second code. When parallel encoders are used, as in turbo coding, two corresponding decoders may conveniently be used in parallel for this purpose. Such iterative decoding is carried out for a plurality of iterations until it is believed that the soft data closely represents the transmitted data. Those bits that have a probability indicating that they are closer to one (for example, between 0 and 31 on the scale described above) are assigned binary zero, and the remaining bits are assigned binary one.
“Turbo coding” represents an important advancement in the area of forward error correction (FEC). There are many variants of turbo coding, but most types of turbo coding use multiple encoding steps separated by interleaving steps combined with the use of iterative decoding. This combination provides previously unavailable performance with respect to noise tolerance in a communications system. Namely, turbo coding allows communications at levels of energy-per-bit per noise power spectral density (Eb/N0) that were previously unacceptable using the existing forward error correction techniques.
Many communications systems use forward error correction techniques and therefore would benefit from the use of turbo coding. For example, turbo codes could improve the performance of wireless satellite links, in which the limited downlink transmit power of the satellite necessitates receiver systems that can operate at low Eb/N0 levels.
Digital wireless telecommunication systems, for example, such as, e.g., digital cellular and PCS telephone systems, also use forward error correction. For example, the Telecommunications Industry Association has promulgated the over-the-air interface standard TIA/EIA Interim Standard 95, and its derivatives, such as, e.g., IS-95B (hereinafter referred to collectively as IS-95), which define a digital wireless communications system that uses convolutional encoding to provide coding gain to increase the capacity of the system. A system and method for processing radio-frequency (RF) signals substantially in accordance with the use of the IS-95 standard is described in U.S. Pat. No. 5,103,459, which is assigned to the assignee of the present invention and fully incorporated herein by reference.
There is an ongoing drive in the communications industry to continually improve coding gains. In conventional digital wireless communications systems, it has been found that a serial interleaver for turbo coding may be advantageously implemented with a congruent random sequence. It is known in the art that a uniform random sequence may be generated by using a linear congruential recursion algorithm. See, e.g., 2 D. Knuth The Art of Computer Programming (1969) (describing generation of pseudo-random numbers with linear congruential recursion). It has also been found that a parallel turbo coder employing a two-dimensional interleaver (i.e., an interleaver organized as a rectangular data array comprising rows and columns) generally outperforms a parallel turbo coder having a one-dimensional interleaver (i.e., an interleaver in which the data is organized as a single, linear array) in terms of coding gain.
It would be advantageous to further enhance the performance of a turbo coder. Additionally, as turbo coders are significantly more complex to implement than are convolutional coders, it would be desirable to provide a turbo coder implementation with reduced complexity. Thus, there is a need for a reduced-complexity, two-dimensional interleaver that uses multiple linear congruential sequences.
Cellular telecommunications systems are characterized by a plurality of mobile transceivers, such as mobile phones, in communication with one or more base stations. Each transceiver includes a transmitter and a receiver.
In a typical transceiver, an analog radio frequency (RF) signal is received by an antenna and downconverted by an RF section to an intermediate frequency (IF). Signal processing circuits perform noise filtering and adjust the magnitude of the signal via analog automatic gain control (AGC) circuitry. An IF section then mixes the signal down to baseband and converts the analog signal to a digital signal. The digital signal is then input to a baseband processor for further signal processing to output voice or data.
Similarly, the transmitter receives a digital input from the baseband processor and converts the input to an analog signal. This signal is then filtered and upconverted by an IF stage to an intermediate frequency. The gain of the transmit signal is adjusted and the IF signal is upconverted to RF in preparation for radio transmission.
The link between a transmitter and a receiver is a channel. One approach to increasing the information-carrying capacity of a channel between a base station and associated mobile stations is to enhance the signal-to-interference ratio (SIR). The SIR is often expressed as a ratio of the energy per information bit received to the interference density of the received signal. To increase system capacity, receivers in the mobile stations and base stations must effectively operate at lower signal-to-interference ratios (SIRs), or the SIR of the channel must be increased. To increase the SIR, the power of the transmitted signal is often increased, which is costly, increases the interference to other mobiles, and, thus, is impractical in many applications. Alternatively, special coding schemes are often employed in order to reduce the required SIR.
Coding for communications signals involves the addition of redundant information to the signals. By strategically adding redundancy to communications signals transmitted in noisy environments, errors introduced by a noisy channel are reduced to a desired level. As shown by Shannon in 1948, if the information rate of the communications signals is less than the channel capacity, the desired noise level is attainable without a reduction of the information rate. If redundancy is not employed in a noisy environment, error-free performance is difficult or impossible to obtain.
Many encoding and decoding systems are designed to control noise and interference related errors that occur during transmission of information in a communications system. Coding is an important consideration in the design of highly reliable modern digital communications systems.
The ability to operate efficiently in noisy or faded environments is particularly important in code division multiple access (CDMA) wireless communications systems where Raleigh-faded signal environments and co-channel interference from other users are common. Raleigh fading results from Doppler frequency shifts in the received signal due mobile station movement. Co-channel interference occurs when a CDMA communications system maintains multiple system users, with each additional user contributing incrementally to the co-channel interference. Co-channel interference is typically larger than other forms of channel noise such as additive white Gaussian noise (AWGN).
In a Raleigh-faded signal environment, the power levels of transmitted communications signals fluctuate in accordance with a Raleigh distribution. The power typically fluctuates over a dynamic range of 10 dB to 50 dB. The duration of the fades is a function of the velocity of a mobile station, i.e., cellular telephone, the frequency channel assigned to the mobile station, and overall signal environment. As the velocity of a mobile unit increases, fade duration decreases, leading to shorter error bursts. As the velocity of the mobile unit decreases, fade duration increases, leading to longer error bursts.
To improve the performance of a wireless communications system in a noisy and Raleigh-faded environment, interleavers following signal encoders are often employed. An interleaver spreads the codewords output from an encoder so that individual bits of a given codeword are separated from each other and transmitted at different times. As a result, individual bits of a given code experience independent fading, where the bits affected by an error burst belong to several codewords. At the receiver, the received signal samples are deinterleaved before decoding. Thus, the effect of the error burst is spread over the message so that it is possible to recover the data with the original error-correcting code. Several types of interleavers exist, including diagonal, convolutional, interblock, and block interleavers.
Turbo codes are serial or parallel concatenations of two or more constituent codes, separated by one or more code interleavers. Turbo encoders and decoders are often employed to improve error control and to reduce the required SIR. Turbo codes are often decoded with a relatively efficient iterative algorithm to achieve low error rates at signal-to-noise (SNR) ratios approaching the Shannon limit. As an essential part of the Turbo code, code interleavers and deinterleavers must be inserted between the component code encoders and decoders, respectively. The performance of turbo codes depends on the length and structure of the code interleavers. Good turbo code performance has been achieved in the past using interleavers having pseudo random structures.
U.S. patent application Ser. No. 09/205,511, filed Dec. 4, 1998 by D. Rowitch et al. and entitled TURBO CODE INTERLEAVER USING LINEAR CONGRUENTIAL SEQUENCES now U.S. Pat. No. 6,304,991, issued Oct. 16, 2001 to Rowitch et al., the teachings of which are incorporated herein by reference, discloses and claims a particularly advantageous interleaver design. The interleaver of Rowitch et al. offers numerous benefits based on simulations running on personal computers. Nevertheless, there is a need to implement the interleaver efficiently in hardware (i.e., cellular telephones).
Hence, a need remains in the art for a system or method for implementing the teachings of Rowitch et al. efficiently in hardware such that the teachings can be incorporated into an integrated circuit or chip that could be used in a cellular phone.